Charles Elkan

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Timothy BaileyUniversity of Nevada, RenoVerified email at unr.edu
Zachary C. LiptonAssistant Professor at Carnegie Mellon University; Chief Scientific Officer at AbridgeVerified email at cmu.edu
Aditya Krishna MenonResearch Scientist, GoogleVerified email at google.com
Bianca ZadroznyIBM Research BrasilVerified email at br.ibm.com
Balakrishnan NarayanaswamyPrincipal ML Scientist, AWS AI, AmazonVerified email at amazon.com
David KauchakAssociate Professor of Computer Science, Pomona CollegeVerified email at pomona.edu
Ramon HuertaSenior Principal Scientist, AmazonVerified email at amazon.com
Qinghua GuoPeking UniversityVerified email at pku.edu.cn
Garrison W. CottrellProfessor of Computer Science and Engineering, University of California, San DiegoVerified email at ucsd.edu
Russ GreinerProfessor of Computer Science, University of AlbertaVerified email at ualberta.ca
Lotfi A. ZadehProfessor Emeritus, EECS, UC BerkeleyVerified email at eecs.berkeley.edu
Padhraic SmythProfessor, Computer Science, University of California IrvineVerified email at ics.uci.edu
Gabriel DoyleAssistant Professor, San Diego State UniversityVerified email at sdsu.edu
Sanmay DasProfessor of Computer Science, George Mason UniversityVerified email at gmu.edu
Douglas TURNBULLAssociate Professor, Ithaca CollegeVerified email at ithaca.edu
Bing LiuDistinguished Professor, University of Illinois at ChicagoVerified email at uic.edu
Joseph SmarrStanford UniversityVerified email at alumni.stanford.edu
Sameer AgarwalGoogle Inc. & University of WashingtonVerified email at google.com
Abhishek KumarStaff Research Scientist at FacebookVerified email at fb.com
Qiang Yang (杨强）Chief AI Officer@WeBank, Chair Prof.@HKUST, IJCAI President 2017-19, AAAI-21 General ChairVerified email at cse.ust.hk

Charles Elkan

Professor of Computer Science, University of California, San Diego

Verified email at ucsd.edu

Machine Learning Data Science Finance


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Fitting a mixture model by expectation maximization to discover motifs in biopolymers TL Bailey, C Elkan ISMB, 28-36, 1994	5852	1994
The foundations of cost-sensitive learning C Elkan International joint conference on artificial intelligence 17 (1), 973-978, 2001	2726	2001
A critical review of recurrent neural networks for sequence learning ZC Lipton, J Berkowitz, C Elkan arXiv preprint arXiv:1506.00019, 2015	2531	2015
Learning the k in k-means G Hamerly, C Elkan Advances in neural information processing systems 16: proceedings of the …, 2004	1236	2004
Learning to diagnose with LSTM recurrent neural networks ZC Lipton, DC Kale, C Elkan, R Wetzel arXiv preprint arXiv:1511.03677, 2015	1187	2015
Transforming classifier scores into accurate multiclass probability estimates B Zadrozny, C Elkan Proceedings of the eighth ACM SIGKDD international conference on Knowledge …, 2002	1186	2002
Using the triangle inequality to accelerate k-means C Elkan Proceedings of the 20th international conference on Machine Learning (ICML …, 2003	1118	2003
Learning classifiers from only positive and unlabeled data C Elkan, K Noto Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008	1087	2008
Unsupervised learning of multiple motifs in biopolymers using expectation maximization TL Bailey, C Elkan Machine Learning 21 (1), 51-80, 1995	960	1995
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers B Zadrozny, C Elkan ICML, 609-616, 2001	923	2001
The value of prior knowledge in discovering motifs with MEME. TL Bailey, C Elkan Ismb 3, 21-29, 1995	895	1995
The field matching problem: algorithms and applications AE Monge, C Elkan KDD 2, 267-270, 1996	889	1996
Alternatives to the k-means algorithm that find better clusterings G Hamerly, C Elkan Proceedings of the eleventh international conference on Information and …, 2002	729	2002
Link prediction via matrix factorization AK Menon, C Elkan Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011	653	2011
Learning and making decisions when costs and probabilities are both unknown B Zadrozny, C Elkan Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001	619	2001
An efficient domain-independent algorithm for detecting approximately duplicate database records AE Monge Proc. of the ACM-SIGMOD Workshop on Research Issues on Knowledge Discovery …, 1997	602	1997
The transporter classification database: recent advances MH Saier Jr, MR Yen, K Noto, DG Tamang, C Elkan Nucleic acids research 37 (suppl_1), D274-D278, 2009	480	2009
The paradoxical controversy over fuzzy logic C Elkan IEEE Intelligent Systems, 47-49, 1994	467*	1994
The paradoxical success of fuzzy logic C Elkan, HR Berenji, B Chandrasekaran, CJS De Silva, Y Attikiouzel, ... IEEE Expert 9 (4), 3-49, 1994	465	1994
Results of the KDD'99 classifier learning contest C Elkan ACM SigKDD Explorations Newsletter 1 (2), 63-64, 2000	400	2000

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